Video image standards for spatial and temporal resolution are based mainly on an acceptable picture quality for human observers. These video images contain extremely large amounts of information (approximately 100 Mbits/sec for moving digital video images) and require very large bandwidths. This necessitates the use of costly communication channels for transmission with consequent increase of pressure and demand on available communication bandwidths in both space and terrestrial systems. Additionally the storage of such large amounts of information requires the use of costly, large and heavy storage means.
It has previously been proposed to reduce the amount of data transmitted by making use of the fact that a proportion of the data necessary for each successive frame of a moving picture is common to adjacent frames and need not be transmitted for each frame. Such redundant data can be eliminated and conventionally this is done by image compression techniques which utilize combinations of established methods such as predictive, transform, conditional replenishment and vector quantisation algorithms.
These proposed image compression techniques all suffer from various drawbacks. For example a proposed hybrid coding technique using motion compensated prediction followed by a discrete cosine transform on the prediction errors results in degradations such as block busyness, low resolution of moving areas, and difficulty in disguising the artefacts of the algorithm used.